Radiation therapy (RT) is a popular and efficient method for cancer treatment, where ionizing radiation is used in an attempt to kill malignant tumor cells or to slow down their growth. RT is often combined with surgery, chemotherapy, or hormone therapy, but may also be used as a primary therapy mode. Radiation therapy may be administered as internal RT or brachytherapy or, more commonly, external beam RT.
Internal RT treatment typically includes placing one or more radioactive sources near a designated treatment area, either permanently or temporarily. Conversely, external beam RT typically involves directing radiation beams produced by sources located externally with respect to the patient or radiation subject to the afflicted treatment area. The beam can consist of photons, electrons, protons or other heavy ions; photons being (at present) the most commonly used particle type. Malignant cells are damaged by the ionizing radiation used during the RT. However, the damage from the radiation is not limited to malignant cells and thus, the dosage of radiation to healthy tissues outside the treatment volume is ideally minimized to avoid being similarly damaged.
The development of medical linear accelerators (linacs) have dramatically increased the practicality and efficiency of multi-field RT treatments. Even more recently, computer-controlled hardware such as the multi-leaf collimator (MLC) have been developed that deliver fields conforming to the projection of the target with even greater ease. In more advanced applications, the individual leaves of the MLC are moved separately under computerized control at desired speeds during periods of radiation (e.g., beam-on). This has enabled the generation of spatially modulated radiation fields, since each leaf attenuates the beam for a different time period. The resulting intensity modulated radiotherapy (IMRT) has allowed the application of high dose volumes that conform more closely to the shape of complicated targets. The further integration of x-ray image receptors to the linac has enabled the imaging of the patient before each treatment session and the tracking of tumor motion during treatment delivery. These so-called image-guided RT methods have improved subject positioning accuracy, and have lead to techniques for restricting tumor motion during treatment.
The purpose of traditional RT treatment planning methodologies is to devise a treatment regimen which produces as uniform a dose distribution as possible to the target volumes whilst minimizing the dosage outside this volume. It is crucial to successful radiation therapy that the discrepancies between dose distributions calculated at the treatment planning stage and those delivered to the patient are minimized. Thus, calculating precise levels of radiation at the treatment planning stage is of utmost importance. In conventional radiation therapy treatment planning systems, the radiation is calculated first in the geometry of the particular radiation source (e.g., external or internal), followed by tracking the transport and energy deposition in the particular target volume and/or area of interest.
In radiation therapy, the distribution of particles emanating from a treatment unit given on a plane (e.g. orthogonal to the central axis) is defined as phase-space. At each pixel on the plane, the distribution of each particle type in energy and direction of propagation is given. Conventionally, the primary radiation beam entering the patient (the primary component of the phase space) is often expressed using a two dimensional energy fluence array together with an energy spectrum. The energy spectrum describes the distribution of the beam energy to different energy ranges. In a general case, the energy spectrum also varies spatially within the beam. While the primary photon beam accounts for the vast majority of the energy fluence that enters the patient, there may be other additional contributions as well. Scattered photons may originate from the primary collimator and the flattening filter. In addition, electrons produced in the air as well as other parts of the accelerator may also contaminate the beam. These scattered photons may, in the aggregate, detrimentally affect the accuracy of a calculated dosage, if they are not modeled in the calculation. In order to model the effect of the scattered photons, the phase space of the scattered photons must be modeled separately to more accurately determine the total phase space of the radiation beam.
Unfortunately, the phase-space of the scattered photons cannot be accurately described using a two-dimensional energy fluence, because the energy fluence passing through a plane orthogonal to the beam axis depends on the distance from the target in a non-trivial way (or equivalently, not all scattered photons are traveling in a line emanating from the primary source). One solution to this problem is to use a plurality of two-dimensional energy fluences at different distances from the target (a 3D-fluence) to model the head scatter phase space. For a static beam (when neither the MLC nor collimator jaws move), the 3D energy fluence can be calculated by tracing the ray from a two-dimensional source located in the treatment head (e.g. at the bottom level of the flattening filter), taking into account the positions of the collimating jaws and the opening ratio matrix (ORM) defined by the MLC leaves.
During the delivery of an intensity modulated radiotherapy (IMRT) treatment, the MLC leaves, the collimator jaws, or both may be moving. In typical treatment planning systems this motion is represented using a plurality of control points. These control points also control the movement of the corresponding components of the linac. Under these circumstances, the 3D-fluence should (in principle) be calculated for each control point. However, if the jaws are static and only the MLC leaves move, an adequate approximation can be obtained by only using the two-dimensional ORM of the primary photon beam and the static jaw positions as input. However, if the jaws also move, it is necessary to calculate the 3D fluence for a plurality of jaw positions. There can be several hundred jaw positions in the set of control points for a typical clinical IMRT field. Such a field may consist of multiple static segments or it may be a sliding window beam with jaw-tracking. Unfortunately, calculating the 3D-fluence for each of these jaw positions can be extremely time consuming, and will result in a much longer dose calculation time. In addition, there is currently no simple way to deduce an ORM of the MLC separately for each jaw-opening based on the total ORM of the control point sequence only.
Under conventional techniques, the contribution of head scatter has been calculated either in a very approximate manner (using a single jaw-opening) or using a very CPU-intensive (slow) method (using all jaw-openings). Under such techniques, using the single-jaw-opening for a head-scatter contribution calculation is very likely to decrease the accuracy of the dose calculation, often significantly. On the other hand, calculating the contribution of head scatter by using every jaw-opening results in a higher degree of accuracy, but can be very time and resource intensive, resulting in inefficient processing.